Optimal Operation of Distribution Networks Considering Renewable Energy Sources Integration and Demand Side Response - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Sustainability Année : 2023

Optimal Operation of Distribution Networks Considering Renewable Energy Sources Integration and Demand Side Response

Ahmed Hachemi
Fares Sadaoui
Mohamed Ebeed
Hossam Abbou

Résumé

This paper demonstrates the effectiveness of Demand Side Response (DSR) with renewable integration by solving the stochastic optimal operation problem (OOP) in the IEEE 118-bus distribution system over 24 h. An Improved Walrus Optimization Algorithm (I-WaOA) is proposed to minimize costs, reduce voltage deviations, and enhance stability under uncertain loads, generation, and pricing. The proposed I-WaOA utilizes three strategies: the fitness-distance balance method, quasi-opposite-based learning, and Cauchy mutation. The I-WaOA optimally locates and sizes photovoltaic (PV) ratings and wind turbine (WT) capacities and determines the optimal power factor of WT with DSR. Using Monte Carlo simulations (MCS) and probability density functions (PDF), the uncertainties in renewable energy generation, load demand, and energy costs are represented. The results show that the proposed I-WaOA approach can significantly reduce costs, improve voltage stability, and mitigate voltage deviations. The total annual costs are reduced by 91%, from 3.8377 × 107 USD to 3.4737 × 106 USD. Voltage deviations are decreased by 63%, from 98.6633 per unit (p.u.) to 36.0990 p.u., and the system stability index is increased by 11%, from 2.444 × 103 p.u. to 2.7245 × 103 p.u., when contrasted with traditional methods.

Dates et versions

hal-04538463 , version 1 (09-04-2024)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Ahmed Hachemi, Fares Sadaoui, Abdelhakim Saim, Mohamed Ebeed, Hossam Abbou, et al.. Optimal Operation of Distribution Networks Considering Renewable Energy Sources Integration and Demand Side Response. Sustainability, 2023, 15 (24), pp.16707. ⟨10.3390/su152416707⟩. ⟨hal-04538463⟩
6 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More